An Optimal Adsorption Force Planning Method for Wheeled Climbing Robot on Large Components With Curved Surfaces

The wheeled negative pressure adsorption climbing robots possess unique advantages for processing extra-large components due to the surface adsorption and motion ability. The large components usually have complex variable curvature surfaces, significantly amplifying the propensity for wheel slip of climbing robots. An adsorption forces planning method was proposed to restrain the slip and then approach stable motion. To address adsorption forces planning demand, we propose a motion performance indicator associated with the wheels’ slip, and establish a dynamic model based on the nonlinear tire model, revealing the quantified effect of adsorption forces on slip ratios. Furthermore, a constrained optimization problem is established to solve optimal adsorption forces using the particle swarm optimization. The proposed method has been validated adequately on a part of a large wind turbine blade, which is a typical large component with variable curvature. The results show a great performance upgrade, the average and the standard deviation of the slip ratios were reduced by 73% and 70% at maximum, respectively. Additionally, the error of yaw angles was reduced by 84% at maximum. The experiment demonstrates the proposed method greatly improves motion performance.